非机动车骑行者不安全行为风险感知研究

发布时间：2018-04-20 08:21

本文选题：非机动车 + 不安全行为　；参考：《北京交通大学》2015年硕士论文

【摘要】：非机动车出行有方便、快捷、环保等优点,故受到各国政府的大力支持,越来越多的人选择非机动车出行。然而,在城市交通中,非机动车是弱势群体,涉及非机动车的交通事故越来越多。如何减少非机动车交通事故,提高非机动车出行的安全性已成为全社会关注的重点问题,研究非机动车的交通安全问题具有十分重要的意义。自行车和电动车作为两类不同的出行方式,在行为和安全性能等方面存在显著差别,很少有文献对两种交通方式的安全性进行详细比较。存在不安全行为时不同车辆之间的碰撞直接导致了事故的发生,不同危险场景下碰撞风险感知的比较在现有文献中很少涉及。据此,本文以非机动车为主要研究对象,采用多元logistic模型、因子分析和结构方程模型等方法,探究自行车和电动车的不安全行为及其风险感知等问题。具体的研究工作如下： (1)结合调查数据,研究非机动车骑行者在个人属性、骑行属性及安全属性等方面的分布特点,并比较了自行车与电动车的差异。结果表明已婚、全职、女性的骑行者选择电动车出行要多于自行车。电动车事故率要明显高于自行车。两类车型骑行者在骑行距离、出行目的、事故责任方等方面也存在一定的差异。在实际管理、使用和政策制定等方面应该对两种车型有所区别。 (2)研究骑行者对不同交通方式安全性感知,应用多元logistic回归的方法,建立交通方式安全感知模型。结果发现有驾照的骑行者认为电动车比自行车安全的概率是无驾照骑行者的4.15倍,认为开车比自行车安全的概率是无驾照者的3.16倍。已婚的骑行者、男性骑行者认为开车和电动车出行比自行车安全；相反,单身的骑行者、女性骑行者则认为自行车出行更安全。此外,年龄、目前所使用的交通工具等因素对交通方式安全性感知也有显著影响。 (3)研究不同危险情形下碰撞风险感知的差异,结合因子分析结果建立碰撞风险感知结构方程模型。根据风险感知得分分析,与速度较快车辆(小汽车、电动车)发生碰撞时风险感知较高；同样情形下自己违规时,碰撞风险感知会降低。根据结构方程模型结果,不安全行为或不安全倾向增多时,感知碰撞风险会下降；主观规范提升时,感知碰撞风险会相应升高。本文利用SPSS统计分析软件对调查数据进行分析,研究非机动车的交通安全问题,最后结合各部分研究结果,对如何提高非机动车行驶安全性,提出了各种合理有效的建议。
[Abstract]:Non motor vehicle travel has the advantages of convenience, shortcut, environmental protection and so on. Therefore, more and more people choose non motor vehicles to travel. However, in urban traffic, non motor vehicles are vulnerable groups and more and more accidents involving non motor vehicles are involved. Integrity has become a major concern of the whole society. It is of great significance to study the traffic safety problem of non motorized vehicles.
As two different modes of travel, bicycles and electric vehicles have significant differences in behavior and safety performance. Few documents compare the safety of the two modes of traffic in detail. The collision between different vehicles directly leads to the occurrence of accidents when there is unsafe behavior, and the risk perception of collision in different dangerous scenes. The comparison is rarely involved in the existing literature. According to this, this paper takes the non motor vehicle as the main research object, uses the multiple logistic model, the factor analysis and the structural equation model to explore the unsafe behavior and risk perception of the bicycle and the electric vehicle.
(1) according to the survey data, the distribution characteristics of non motor vehicle riders in personal attributes, riding properties and safety attributes are studied, and the differences between bicycles and electric vehicles are compared. The results show that married, full-time and female riders choose to travel more than bicycle. The accident rate of electric vehicles is obviously higher than that of bicycles. Two types of cars are more than bicycles. There are also certain differences in riders' riding distance, travel purposes, and accident liability parties. The two types of models should be different in actual management, use and policy formulation.
(2) to study the safety awareness of riders on different modes of traffic and use the multiple logistic regression method to establish a traffic safety perception model. The results show that a rider with a driver's license is 4.15 times more likely to be safer than a bicycle and that the probability of opening a car is 3.16 times more likely to be safer than a non driver. For married riders, male riders think driving and electric car travel are safer than bicycles; on the contrary, single riders and female riders think bicycles are safer. In addition, age, and current means of transportation have a significant impact on traffic safety.
(3) to study the difference of risk perception in different dangerous situations, and to establish the structural equation model of collision risk perception with the result of factor analysis. According to the risk perception score, the risk perception is higher when the speed vehicle (car, electric vehicle) collides with the risk perception score. In the same case, the collision risk perception will be reduced. As the result of the structural equation model, the perceived collision risk will decrease when the unsafe behavior or insecurity tendency increases, and the perceived collision risk will rise correspondingly when the subjective norm is raised.
In this paper, the SPSS statistical analysis software is used to analyze the survey data and to study the traffic safety of non motor vehicles. Finally, in combination with the results of various parts, this paper puts forward all kinds of reasonable and effective suggestions on how to improve the safety of non motor vehicles.

【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：U491

【参考文献】